Introduction:
Alan Kay shares his thoughts on computer science education at universities and emphasizes that his opinions may be limited due to his experiences and research interests.

McLuhan’s Probes and Computer Science Education:
Alan Kay discusses the concept of “probes” introduced by media theorist Marshall McLuhan. He suggests that McLuhan’s approach to stimulating thought and exploring paradoxical ideas is relevant to computer science education.

Challenges in Computer Science Education:
Kay highlights the scale and commercialization of computing, leading to curriculum focused on details rather than fundamental concepts. He argues that computer science has not yet matured as a field and lacks the characteristics of a well-established science.

Curriculum Design: The Example of Music:
Kay emphasizes the importance of designing curricula that focus on content and meaningful learning, rather than rote memorization of details. He draws parallels to music education and the challenges of designing a curriculum that captures the essence of music rather than focusing on technical exercises.

The Decline of Performance Majors in Music:
Kay discusses the phasing out of performance majors in music at UCLA in favor of musicology due to the emphasis on papers and certification. He emphasizes the importance of practical skills and the difficulty of assessing performance through traditional academic means.

Marvin Minsky’s Critique of Computing:
Kay refers to Marvin Minsky’s Turing Award speech in 1970, where Minsky criticized the obsessive concern with form over content in computing. He highlights the relevance of this critique to the current state of computer science education.

Neil Postman’s Book “Amusing Ourselves to Death”:
Kay mentions Neil Postman’s book “Amusing Ourselves to Death,” which examines the impact of media and technology on public discourse. He suggests that today’s information overload and distraction could be characterized as “Distracting Ourselves to Death.”

Challenges in Finding Researchers for a Research Project:
Kay shares his experience in searching for researchers for a research project and notes that most of the suitable candidates were not from the US. He emphasizes the need for researchers with a different outlook, who are greatly dissatisfied and able to work through depression and anxiety.

Smartness and Leonardo da Vinci:
Kay discusses the idea of smartness and its limitations in the context of historical figures like Leonardo da Vinci. He suggests that even individuals with extraordinary intelligence are constrained by the knowledge and technology available during their time.

Outlook, Perspective, and Epistemological Framework:
Schools should focus on teaching outlook, perspective, and epistemological frameworks rather than just IQ or knowledge. Knowledge is abundant, but the perspective and framework to understand and apply it are crucial.

Montessori Education:
Montessori education emphasizes developing children’s common sense to be in line with the current era, not outdated notions. Common sense among high school and college students often resembles that of cave people.

Community Science:
Traditional computer science research and education produce brilliant researchers but lack the desired approach for real-world impact. Community science involves working with people who have different perspectives and backgrounds, valuing diversity and collaboration.

Universities’ Focus:
Universities tend to focus on publishing papers and attending conferences rather than addressing real-world problems. There is a need to bridge the gap between academic research and practical applications.

Technology’s Impact on Education:
Technology has the potential to transform education by providing access to diverse perspectives and facilitating collaboration. Online communities and networks can foster learning and knowledge sharing beyond traditional classroom settings.

Conclusion:
Alan Kay emphasizes the importance of outlook, perspective, and epistemological frameworks in education. He advocates for community science and values diversity and collaboration in problem-solving. Technology can play a significant role in transforming education and facilitating access to knowledge and collaboration.

Why Are Computers Today Less Efficient Than Those at Xerox PARC?:
Xerox PARC’s computers were 1,000 times more efficient than today’s computers. Moore’s law and the Turing tar pit are not compensating for bad computing. PARC’s success was due to its advanced computer architecture and the ability to experiment without optimization.

Xerox PARC’s Computer Architecture and Its Advantages:
It was 15 years ahead of its time, enabling experimentation and advanced application development. The Alto computer was 50 times faster than a time-sharing terminal, allowing for rapid prototyping and testing. Optimizing code on the Alto resulted in applications comparable to those developed 10 years later.

Xerox PARC’s Research and Its Impact on Modern Computing:
Xerox PARC’s research was easily portable and optimized on various platforms. Benchmarks showed that today’s computers are only 50 times faster than Xerox PARC’s computers. Memory architectures and caching techniques have not kept pace with Moore’s law, resulting in slower performance. Xerox PARC’s microcoded hardware enabled fast virtual machines for high-level languages.

Alan Kay’s Approach to Team Building and Education:
Alan Kay values individuals with contradictory elements on their resumes, indicating a willingness to think differently. He favors intern programs, as transcripts may not accurately reflect an individual’s potential. Kay believes in hands-on experience and experimentation rather than traditional academic qualifications.

Background:
Alan Kay earned his PhD at an ARPA project and gained insights into their unique approach to evaluating students.

Dave’s Theory:
Dave, a key figure in the ARPA project, believed in granting access to anyone showing potential, regardless of formal qualifications. Students were given a two-year trial period to demonstrate their abilities.

Faculty Evaluation:
After two years, the faculty would collectively assess each student’s progress and determine their suitability for a PhD. Those deemed unsuitable would fail their oral exams and receive a master’s degree, while those deemed promising would continue towards a PhD.

Utah’s Approach to PhD:
At the University of Utah, two years of exceptional work contributing to the field were considered sufficient for a PhD, regardless of completion.

Alan Kay’s Experience:
Kay was able to complete his PhD in two and a half years due to the quality of his work on personal computing. He highlights the contrasting approaches to graduate admissions at other institutions, where he would not have been accepted as a student.

Identifying Talented Individuals:
Kay emphasizes the importance of recognizing potential in individuals who may not fit traditional academic criteria. He shares an example of an enthusiastic Australian student who traveled to meet Kay and express his interest in their project.

Evaluating Deep Understanding:
Kay expresses concern that the Australian student may be more of a “hacker” than a deep thinker, which could limit his contributions to their project. The internship period will serve as an opportunity to assess the student’s ability to engage with complex concepts.

Ambiguity of the Project:
The details of the project remain undisclosed, leaving the reader curious about its nature and objectives.

Background:
Alan Kay received $1 million per year for five years from NSF and an equal amount from another funder for a project called “Steps Towards the Reinvention of Programming.” The project aims to create an alternative basis for an entire computing system that is less complex and more expressive.

Project Goals:
To develop a new programming paradigm that is significantly different from traditional approaches. To explore new ways of coupling large numbers of things loosely. To reduce the amount of code required to create a personal computing experience by two to three orders of magnitude. To increase the expressiveness of software through Moore’s Law.

Key Ideas:
Publish and subscribe messaging as an alternative basis for programming. Fast forward inference for pattern-matched, event-driven programming. Field programmable gate arrays for changing fundamental assumptions about programming. Eliminating procedure calls for a different way of coupling. Creating an entire personal computing experience with less than 20,000 lines of code.

Challenges:
The project is ambitious and there is a high chance of failure. Some of the proposed principles are not yet fully understood and may require breakthroughs. The project requires a long-term commitment of funding and resources.

Timeline:
The project is expected to take three years to complete if fully funded for five years. If funded for only two years, it is likely to take 10 years. If funded for three years, it is likely to take five years.

Significance:
The project has the potential to revolutionize the way we think about programming and computing. It could lead to the development of new programming languages, tools, and architectures. It could make computing more accessible and powerful for everyone.

Programmers and Coping:
Alan Kay emphasizes that successful programmers must be good at coping, as they often work with various machines, software, compilers, etc., that may be flawed or inconvenient.

The Art of Programming Language Design:
According to Kay, designing a programming language involves experiencing physical discomfort while using a language that one finds ugly. Being content with coping hinders the ability to design good programming languages.

PARC’s Culture of Criticism:
Xerox PARC was known for its critical and argumentative atmosphere, where people openly discussed the shortcomings of existing technologies, including their own. This culture facilitated innovation and improvement.

The Decline of Criticism in the Internet Age:
Kay observes that the internet has led to a decline in meaningful criticism due to the abundance of unfounded criticism. This makes it challenging to engage in productive discussions and identify genuine problems.

Misconceptions about Darwinian Processes:
Kay highlights the misconception that the current state of technology is the best possible outcome due to the participation of many individuals. He emphasizes that Darwinian processes are not optimizers but satisficers, which means they find solutions that are good enough, not necessarily the best.

Studying Programmers vs. Studying Programming:
Kay disagrees with the idea of studying programmers and their behavior to inform language design. He believes that studying programming itself, its fundamental principles, and its historical context is more valuable for language design.

Underlying Principles of Personal Computing:
The true computer revolution is yet to happen, and we should avoid drawing analogies from current practices. User interfaces should prioritize learning and adaptability, catering to future capabilities beyond initial functions. Personal computing requires children’s inclusion, as they drive the need for user-friendly and intuitive interfaces.

The Significance of Anthropology:
Anthropology is crucial for developing a broader perspective and understanding of different cultures, preventing self-seriousness and cultural biases. Modern biology offers insights into scaling and transitioning from strongly coupled to weakly coupled systems.

The Internet and Ethernet:
The internet and ethernet, products of the ARPA community, represent a paradigm shift in computing. These technologies embody the principles of decentralization, distributed objects, and no central control.

The Decentralized Architecture:
The decentralized architecture promotes personal computing, distributed objects, and a lack of central control in programming languages, applications, and operating systems. The romantic idea of decentralization contrasts with the current state of computing, where centralized architectures still dominate.

The Need for Standards:
The proliferation of inefficient and poorly designed code poses a challenge. Enforcing standards through a governing body is not the solution, as it stifles innovation and creativity.

The Internet’s Example:
The internet’s success lies in its adherence to standards and protocols, enabling interoperability and widespread adoption. Drawing inspiration from the internet’s principles can guide future developments in computing.

Encapsulation of Objects:
The internet is a unique example of a real object system where each object is an entire computer, providing strong encapsulation. Each object receives pure messages, ensuring that any crashes or errors are the sole responsibility of the receiving object, not the sender.

Decentralized Responsibility:
Developers should strive to create encapsulated objects that can operate independently. The internet demonstrates the power of decentralized responsibility, where each object can decide how to respond to messages without relying on a central authority.

Interoperability and Reusability:
The internet’s pure messaging system allows objects to communicate seamlessly, regardless of their operating system or platform. This interoperability and reusability promote collaboration and innovation.

Importance of Virtual Machines:
To maximize the number of encapsulated objects within a single machine, developers should embrace virtual machines. Virtual machines provide confinement, allowing multiple operating systems and applications to run concurrently and securely.

Alan Kay’s Views on Computer Science and Software Architectures:
Kay criticizes Intel’s architecture for not prioritizing certain features, such as virtual address spaces, inter-process messaging, and microcoding, which hinder the development of operating systems and software. He emphasizes the importance of confinement, facilities, and services in software architectures and calls for real confinement rather than relying solely on software for security. Kay highlights the significance of historical knowledge in computing, particularly the work of pioneers like Bob Barton and Engelbart, which is often overlooked in computer science education. He questions the validity of computer science as a field due to its lack of focus on building upon past knowledge and its tendency to prioritize IQ over a comprehensive understanding of computing history and principles. Kay criticizes the pop culture’s obsession with identity and the lack of interest in the past and the future, which he believes hinders the progress of computer science. He asserts that the primary purpose of an educational institution should not be to teach but to facilitate learning and exploration, as there is too much knowledge to teach within the traditional educational model.

Educational Purpose:
The primary goal of education is to aid students in understanding quality thresholds.

Differentiating Real Disciplines from Bullshit:
For a field to be considered a legitimate discipline, it must meet certain quality standards. Work that falls below the threshold is superficial and meaningless. It is the university’s responsibility to ensure that only high-quality work is recognized and rewarded.

PhD Standards in ARPA-Supported Universities:
In the 1960s, ARPA-funded universities held rigorous standards for PhDs. A PhD could only be obtained by advancing the state of the art in a tangible way. Alan Kay suggests implementing this criterion across all PhD programs.

Curriculum Battles in the 1970s and 1980s:
There was a significant debate regarding the undergraduate curriculum in American universities. The outcome favored a curriculum focused on algorithms and data structures, neglecting systems thinking. This shift has had a lasting impact on computing education.

Teaching Architects and Stonemasons Together:
Alan Kay draws a parallel between teaching architects and stonemasons in the same classroom. He questions the effectiveness of teaching individual technologies and skills over foundational concepts.

Historical Perspective on Teaching Programming:
Historically, programming was taught as a vocation, separate from the science of computing. Alan Kay believes that this approach may have contributed to the current state of computer science education.

Historical Context:
In the early 1960s, programming was a niche field with a significant number of female programmers, who were later marginalized as the profession gained popularity. In Japan, programming was initially considered a low-class profession.

Separation of Roles:
During that era, programmers primarily created flowcharts, while coders translated those flowcharts into code, resulting in a clear distinction between architects and implementers.

Critique of Current Practices:
Alan Kay criticizes the reliance on specifications that cannot be executed, emphasizing the need for debuggable architectures.

Design vs. Optimization:
Kay highlights the distinction between design and optimization, suggesting that focusing on both simultaneously can be challenging. He proposes a separation between architects and optimizers to maintain a clear division between design and implementation.

12 Principles:
One of the 12 principles in Kay’s approach is to separate the meanings of things from their optimizations, allowing for debugging and verification of the intended functionality.

Metaphor of Stonemasons:
Kay compares the current state of computer science to a colonization by stonemasons, referring to the dominance of low-level programming techniques and the lack of focus on architecture.

Architecture in Academia:
Kay criticizes the lack of emphasis on architecture in academia, highlighting the need for institutions that create things that require architectural thinking. He emphasizes that architecture is not a theoretical concept but requires practical experience to truly understand it.

The Importance of Architecture:
Alan Kay emphasizes the significance of architecture in shaping the properties and capabilities of a system. He draws an analogy between building with bricks and constructing an arch, highlighting that the organization and arrangement of materials are crucial for achieving desired outcomes. Kay believes that a 100 million line operating system lacks a well-defined architecture and is merely an accumulation of components, leading to inflexibility and difficulty in modification.

The Advantage of Arches:
Kay stresses the benefits of using arches in construction, such as reduced material requirements and increased reformability compared to pyramids built without arches. He argues that teaching the principles of architecture, including the concept of arches, should start early in childhood to develop a deep understanding and appreciation for scale and structure.

Computational Thinking:
Kay acknowledges the idea of computational thinking as a valuable concept proposed by Jeanette Wing and others. He recognizes the importance of teaching the fundamental principles and innovative approaches that have emerged in computer science over the past few decades.

Critique of Computational Thinking:
Kay expresses concerns about the narrow focus of computational thinking, which he believes promotes the idea that the great inventions of computer science should be infused into all fields. He argues that this approach may overlook the broader value and potential of computing and may not fully address the need for a fundamental shift in thinking and understanding.

Love for Computing:
Kay clarifies his stance on computing, emphasizing his deep passion for the field. He stresses that his criticisms are not intended to diminish the value of computing but rather to encourage a more comprehensive and holistic approach to its study and application.

The Wonders of Technology:
Alan Kay expresses his admiration for technology, particularly computers, and believes it is one of humanity’s greatest inventions. However, he laments that people often fail to appreciate or explore the wonders that technology offers.

Looking Beyond the Past:
Kay emphasizes the importance of looking into the future rather than solely focusing on the past. He criticizes the tendency to rely solely on past knowledge and experiences, which limits progress and innovation.

McLuhan’s Insights:
Kay references Marshall McLuhan’s observations about society’s tendency to focus on the rearview mirror while driving into the future. He also mentions McLuhan’s view that artists can see a bit of the present and the future due to their ability to perceive things that others overlook.

The Power of Refusal:
Kay draws attention to Susan Sontag’s statement that progress begins with refusing to accept the current state of affairs. He highlights the importance of challenging and questioning existing norms and practices to drive progress.

The $100 Laptop Project:
Kay discusses the $100 laptop project, which aimed to make affordable laptops accessible to children in developing countries. He emphasizes the project’s success in demonstrating the feasibility of producing low-cost laptops through collaboration and technological advancements.

Innovation in Display Technology:
Kay mentions the invention of a new display technology for the $100 laptop, led by Mary Lou Jepson. He highlights the significance of this innovation in overcoming challenges related to cost, brightness, and darkness.

Simplicity and Efficiency:
Kay describes the simplicity and efficiency of the $100 laptop’s design, including its low power consumption and the use of treadle power in resource-constrained environments.

Technology’s Potential for Progress:
Kay concludes by emphasizing that the $100 laptop project was not a difficult undertaking, demonstrating the potential for technological progress with determination and collaboration. He challenges the notion that technological advancements are inherently complex and unattainable.

Escaping Conventional Computing Ideas:
Alan Kay believes individuals are trapped in conventional X and Y computing concepts, limiting creativity and innovation. He emphasizes the ease of creating anything, including a working jet engine, with modern technology. The main obstacle is the lack of motivation and willingness to explore new possibilities.

E.E. Cummings’ Poetry as Inspiration:
Speaker 01 suggests studying E.E. Cummings’ poetry as a pathway to the next level of computing. Cummings’ ability to convey big ideas with few words and punctuation is seen as a model for creating more integrated and intelligent computing systems.

Paradoxes and Alternate Dimensions:
Kay explains how paradoxical statements can lead to new insights and dimensions of understanding. He uses the example of an arch, where two opposing forces create a stable structure. He encourages exploring paradoxical ideas to find solutions that are not immediately apparent.

Economic Factors Influencing Computing:
Kay criticizes the current economics of computing, where consumers are unwilling to pay for powerful computers. He emphasizes the importance of investing in high-performance computers that can drive future innovations.

Chuck Thacker’s Work on Field Programmable Gate Arrays (FPGAs):
Kay praises Chuck Thacker, a hardware architect, for his contributions to computing. Thacker’s work on FPGAs has the potential to revolutionize computing by making it more accessible and customizable.

FPGA-Based Research Computer:
Kay envisions a research computer that utilizes FPGAs and is constantly updated with the latest hardware every three years. This approach allows researchers to push the boundaries of computing and explore new possibilities.

Addressing Market Forces in Research:
Speaker 05 raises concerns about marketplace forces limiting innovative research in industry and academia. Kay acknowledges the influence of commercial viability but emphasizes the need for research to focus on advancing knowledge and unearthing powerful ideas, regardless of immediate profitability.

Science vs. Engineering:
Kay distinguishes between science and engineering, highlighting that science aims to advance knowledge, while engineering applies scientific principles to practical problems. He criticizes the conflation of these two fields, leading to a focus on engineering aspects rather than fundamental scientific research.

Encouraging Prototypes and Innovation:
Kay emphasizes the importance of creating working prototypes to demonstrate new concepts and drive innovation. He encourages the exploration of diverse prototypes and challenges researchers to lead him to interesting prototypes they know of.

Conclusion:
Kay concludes by emphasizing the need to challenge conventional computing concepts and explore new possibilities, even if they seem paradoxical or unconventional. He encourages researchers to focus on advancing knowledge and unearthing powerful ideas, rather than being constrained by market forces or traditional approaches.